Discrimination of Brazilian artisanal and inspected pork sausages: Application of unsupervised, linear and non-linear supervised chemometric methods

Food Research International

Volumn 64, Issue , 2014, Pages 380-386

  Matera, J A ^a   Cruz, A G ^a   Raices, R S L ^a   Silva, M C ^a   Nogueira, L C ^a   Quiterio S L ^a   Cavalcanti, R N ^b   Freiras, M Q ^c   Conte Junior C A ^c  

^a INSTITUTO FEDERAL DE EDUCAÇÃO   (Brazil)

^b UNIVERSITY OF CAMPINAS   (Brazil)

^c FLUMINENSE FEDERAL UNIVERSITY   (Brazil)

Author keywords

Artificial neural networks; Chemometric methods; Classification; Pattern recognition; Sausage

Indexed keywords

CHROMATOGRAPHY; CLASSIFICATION (OF INFORMATION); CLUSTER ANALYSIS; COMMERCE; HIERARCHICAL SYSTEMS; MOISTURE; NEURAL NETWORKS; PATTERN RECOGNITION; PRINCIPAL COMPONENT ANALYSIS;

CHEMOMETRIC METHOD; HIERARCHICAL CLUSTER ANALYSIS; MULTIVARIATE TECHNIQUES; NONLINEAR CLASSIFICATION; PARTIAL LEAST SQUARE (PLS); PHYSICOCHEMICAL PARAMETERS; SAUSAGE; SOFT INDEPENDENT MODELING OF CLASS ANALOGIES; PORK SAUSAGES;

MEATS; NEURAL NETWORKS;

EID: 84904695091     PISSN: 09639969     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.foodres.2014.07.003     Document Type: Article

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